CN108520134A - A kind of Engine Noise weight analysis method - Google Patents
A kind of Engine Noise weight analysis method Download PDFInfo
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- CN108520134A CN108520134A CN201810279041.7A CN201810279041A CN108520134A CN 108520134 A CN108520134 A CN 108520134A CN 201810279041 A CN201810279041 A CN 201810279041A CN 108520134 A CN108520134 A CN 108520134A
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- G—PHYSICS
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- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
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- G06F2119/10—Noise analysis or noise optimisation
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Abstract
The invention discloses a kind of Engine Noise weight analysis methods, vibration by test engine multi-state and noise data, adaptive decomposition is carried out to noise signal using variation mode decomposition (VMD) algorithm, original noise is decomposed into the IMF of multiple and different frequency ranges, partial coherence analysis is carried out using the vibration of different structure and the IMF of different frequency range, contribution weight of the different structure to the engine noise under different frequency range, different measuring points, different operating modes is calculated using improvement Fuzzy AHP.
Description
Technical field
The present invention relates to the fields engine NVH, and in particular to a kind of Engine Noise weight analysis method.
Background technology
Currently, country and requirement of the industry laws to vehicle noise are increasingly stringenter, consumer to vehicle noise level and
The requirement of quality is also constantly being promoted.As one of vehicle Main Noise Sources, the noiseproof feature and dynamic property of engine, economy
Property, reliability equally become its main performance index.The noise reduction for carrying out engine needs to be grasped its noise source characteristic, to be directed to
Main Noise Sources are controlled.Engine structure is complicated, noise source is numerous and influences each other, and how to accurately identify and mobilizes owner
It is research emphasis to want noise source.The engine noise source discrimination of generally use includes lead cladding process, coherent analysis, the sound intensity
Method, signal processing method, acoustics imaging method etc..The testing cost of recognition methods based on signal processing is relatively low, flexibility ratio is higher, needle
Corresponding processing method can be selected to signal characteristic, therefore the noise sources identification based on advanced signal processing methods has extensively
Wealthy application prospect.
Some researchers carry out individual signal acquisition by lead cladding process to a certain cylinder of engine, with EEMD
(polymerization empirical mode decomposition)-Roust ICA (robustness independent component analysis)-CWT (continuous wavelet transform) are successfully detached
Go out piston knock noise and combustion noise, and by experimental verification time frequency analysis and blind source separating be combined can effectively into
Row diesel engine noise identifing source.Also the signal of engine head is carried out EEMD decomposition by some researchers, uses vibration signal
Coherent Power Spectrum Analysis is carried out with the IMF (intrinsic mode functions) after decomposition, binding hierarchy analytic approach carries out multi-state overall noise
The calculating of contribution degree.These methods improve Noise Sources Identification and the precision and efficiency of weight analysis to a certain extent, but still
Right Shortcomings.
Although EEMD can solve EMD (empirical mode decomposition) algorithms existing for signal decomposition process to a certain extent
Modal overlap and end effect problem, but the white Gaussian noise being added can influence residual components, while it is existing to generate mode division
As.Within the engine, it is rigidly connected between most structures and body, the vibration signal between structure is caused to be relative to each other.For
For the MISO system of correlation, normal coherence analysis is smaller to the recognition reaction of noise source.Although utilizing layer
Fractional analysis can calculate noise weight of the noise source under different frequency range, different measuring points, different operating modes, but traditional level divides
The consistency that analysis method has coordination judgment matrix is difficult to ensure the scarce limit for lacking abundant scientific basis with consistency check standard.Cause
This, need to propose in Engine Noise weight analysis a kind of more system, more comprehensively, more objective method, make an uproar for engine
Acoustic control provides more accurate effective guidance.
Invention content
Purpose of the invention is to overcome the shortcomings in the prior art, provides a kind of based on variation mode decomposition (VMD)-
The Engine Noise weight analysis method of partial coherence analysis (CCSA)-Fuzzy AHP (FAHP) is started by test
The vibration of machine multi-state and noise data carry out adaptive decomposition using variation mode decomposition (VMD) algorithm to noise signal, will
Original noise is decomposed into the IMF of multiple and different frequency ranges, and inclined phase is carried out using the vibration of different structure and the IMF of different frequency range
Dry analysis calculates different structure to starting under different frequency range, different measuring points, different operating modes using Fuzzy AHP is improved
The contribution weight of machine noise.
The purpose of the present invention is what is be achieved through the following technical solutions:
A kind of Engine Noise weight analysis method, includes the following steps:
(1) vibration of acquisition engine machine difference operating mode, noise signal;
(2) VMD decomposition is carried out to noise signal, obtains the IMF of different frequency range, and the IMF of decomposition is subjected to wavelet transformation;
(3) partial coherence analysis is carried out to vibration and noise signal, different knots is determined according to input pantal coherence power spectral amplitude ratio
Weight sequencing of the structure in different frequency range;
(4) total noise of centrifuge step analysis tree is built:First layer destination layer;The second layer is rotating speed layer;Third layer is measuring point layer;
4th layer is frequency range layer;Layer 5 is solution layer;
(5) multi-state noise source weight calculation is carried out:Specifically include following steps:
A) fuzzy judgment matrix is built according to the weight sequencing result of above-mentioned steps (3), calculates different structure to different frequencies
The weight of section noise, since each vibration, noise signal have corresponding measuring point and rotating speed, each structure of engine is in each frequency
Noise weight under section, each measuring point and various rotating speeds is also different;
B) to each measuring point noise signal carry out one third octave analysis, obtain different frequency range different measuring points power
Weight, according to step a) as a result, establishing combining weights matrix, obtains weight of each structure to different measuring points noise;
C) according to step b) as a result, establish combining weights matrix, weight of each structure to different rotating speeds noise is calculated;
D) according to step c) as a result, the combining weights matrix of structure total noise of centrifuge, finally obtains each structure to total noise of centrifuge
Comprehensive weight.
Further, each structure of engine includes oil sump, left body, right body, gear chamber cover, bell housing, cavaera
Cover.
Compared with prior art, advantageous effect caused by technical scheme of the present invention is:
1. the VMD of noise signal decomposes the modal overlap for efficiently solving existing algorithm and occurring, mode division, endpoint effect
The problems such as answering can accurately obtain the IMF of different frequency range.
2.CCSA is suitable for the mono- output model of multi input-with coherent relationships, more can relative to normal coherence analysis (CSA)
The relationship of characterization vibration and noise.
The problem of 3.FAHP effective solutions traditional AHP consistency, makes calculating contribution weight with more science.
Description of the drawings
Fig. 1 is pantal coherence schematic diagram.
Fig. 2 is step analysis tree schematic diagram.
Fig. 3 is Engine Noise weight analysis technology path schematic diagram.
Specific implementation mode
The invention will be further described below in conjunction with the accompanying drawings.
The present invention protects a kind of Engine Noise weight analysis method, includes the following steps:
(1) vibration and noise signals acquire:Work is measured with reference to GB/T 1859-2000 reciprocating internal combustion engine radiation airborne noise
Journey method and simplified method.Test the vibration and noise signals of diesel engine difference operating mode.
(2) VMD of noise signal is decomposed:VMD decomposition is carried out to noise signal, obtains the IMF of different frequency range.And it will decompose
IMF carry out wavelet transformation, can get the decomposed signal of different frequency range noise.VMD be by signal to be decomposed be converted into onrecurrent,
The resolution model of variation mode solves the modal overlap and mode fragmentation problem of EEMD to a certain extent.To noise signal
The IMF that different frequency range can be obtained in VMD adaptive decompositions is carried out, and the IMF of decomposition is subjected to wavelet transformation, it can be found that noise is believed
Number through VMD decomposition efficiently solve modal overlap, mode division, end effect the problems such as, discomposing effect is good.
(3) partial coherence analysis of vibration noise:Partial coherence analysis is suitable for there are the mono- output moulds of the multi input-of correlativity
Type, respectively by oil sump, left body, right body, gear chamber cover, bell housing, valve cover on the basis of step (1) and (2)
Vibration signal and different frequency range noise signal carry out partial coherence analysis, and different structure is determined according to input pantal coherence power spectral amplitude ratio
In the weight sequencing of different frequency range.The mono- output pantal coherence model schematic of multi input-is as shown in Figure 1, wherein Y (t) is diesel engine
The noise signal of different frequency range;X (t) is noise source;Li(f) it is the condition transmission function inputted between X (t) and output quantity, N
(t) it is noise signal.The specific calculating process of the partial coherence analysis of vibration and noise signal is as follows:
A) Fourier transformation carried out to inputted vibration signal X (t) and output noise signal Y (t), X (t), Y (t) → X (f),
Y(f);
B) auto-power spectrum and crosspower spectrum S of input and output signal are calculatedxx, Syy, Sxy;
C) design conditions transmission function Lij, condition auto-power spectrum Sjj·r!, condition crosspower spectrum Sij·r!;
Sij·r!=Sij·(r-1)!-LrjSir·(r-1)! (5)
Sjj·r!=Sjj·(r-1)!-LrjSjr·(r-1)! (6)
D) partial coherence function is calculatedWith input pantal coherence power spectrum Syxi';
(4) total noise of centrifuge step analysis tree is built:First layer is destination layer (total noise of centrifuge weight);The second layer is rotating speed layer
(idling, 1400r/min, 1800r/min, rated speed);Third layer is measuring point layer (front, rear, left and right, top);4th layer is frequency
Section layer (being respectively the frequency range corresponding to IMF1-IMF6);Layer 5 is solution layer (engine primary structure).Step analysis tree is shown
It is intended to as shown in Figure 2.
(5) according to above-mentioned constructed total noise of centrifuge hierarchical tree, the weight of adjacent layer is calculated based on Fuzzy AHP,
Specific calculating process is as follows:
A) structure fuzzy judgment matrix A=[aij]n×n, wherein element is indicated with 0.1-0.9 in matrix, and 0.5 represents two-by-two
It compares of equal importance.
B) it is based on membership functionBy fuzzy judgment matrix A=[aij]n×nIt is converted into fuzzy
Consistency matrix R=[rij]n×n, and calculate the mutual transoid matrix M of R matrixes.
C) the initial weight ω calculated based on least square method0=[ω1ω2···ωn]:
D) final weight value V is calculated:
Step1:ω0Primary iteration value V as weight0;
Step2:Utilize iterative formula Vk+1=MVkAsk | | Vk+1||∞;
Step3:If | | Vk+1||∞-||Vk||∞≤ ε, then final weight value be(10)
(6) multi-state noise source combining weights are carried out to calculate, specifically includes following steps:
1) fuzzy judgment matrix is built according to the weight sequencing result of above-mentioned steps (3), calculates different structure to different frequencies
The weight of section noise, since each vibration and noise signals have corresponding measuring point and rotating speed, oil sump, left body, the right side
The noise weight of body, gear chamber cover, bell housing, valve cover under each frequency range, each measuring point and various rotating speeds is also different;
2) to each measuring point noise signal carry out one third octave analysis, obtain different frequency range different measuring points power
Weight, according to step 1) as a result, establishing combining weights matrix, obtains weight of each structure to different measuring points noise;
3) according to step 2) as a result, establish combining weights matrix, calculate each structure different rotating speeds operating mode noise contribution
Weight;
4) utilization rate and A weighted sound pressure levels based on different rotating speeds operating mode calculate contribution weight of the rotating speed layer to destination layer,
According to step 3) as a result, the combining weights matrix of structure total noise of centrifuge, finally obtains synthetic weights of each structure to total noise of centrifuge
Weight.
Engine Noise weight analysis technology path schematic diagram such as Fig. 3.
The present invention is not limited to embodiments described above.Above the description of specific implementation mode is intended to describe and say
Bright technical scheme of the present invention, the above mentioned embodiment is only schematical, is not restrictive.This is not being departed from
In the case of invention objective and scope of the claimed protection, those skilled in the art may be used also under the inspiration of the present invention
The specific transformation of many forms is made, within these are all belonged to the scope of protection of the present invention.
Claims (2)
1. a kind of Engine Noise weight analysis method, which is characterized in that include the following steps:
(1) vibration of acquisition engine machine difference operating mode, noise signal;
(2) VMD decomposition is carried out to noise signal, obtains the IMF of different frequency range, and the IMF of decomposition is subjected to wavelet transformation;
(3) partial coherence analysis is carried out to vibration and noise signal, determines that different structure exists according to input pantal coherence power spectral amplitude ratio
The weight sequencing of different frequency range;
(4) total noise of centrifuge step analysis tree is built:First layer destination layer;The second layer is rotating speed layer;Third layer is measuring point layer;4th
Layer is frequency range layer;Layer 5 is solution layer;
(5) multi-state noise source weight calculation is carried out:Specifically include following steps:
A) fuzzy judgment matrix is built according to the weight sequencing result of above-mentioned steps (3), calculates different structure and makes an uproar to different frequency range
The weight of sound, since each vibration, noise signal have corresponding measuring point and a rotating speed, each structure of engine is in each frequency range, each
Noise weight under measuring point and various rotating speeds is also different;
B) one third octave analysis is carried out to each measuring point noise signal, obtains different frequency range in the weight of different measuring points, root
According to step a) as a result, establishing combining weights matrix, weight of each structure to different measuring points noise is obtained;
C) according to step b) as a result, establish combining weights matrix, weight of each structure to different rotating speeds noise is calculated;
D) according to step c) as a result, the combining weights matrix of structure total noise of centrifuge, finally obtains each structure to the comprehensive of total noise of centrifuge
Close weight.
2. a kind of Engine Noise weight analysis method according to claim 1, which is characterized in that each structure packet of engine
Include oil sump, left body, right body, gear chamber cover, bell housing, valve cover.
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CN109917287A (en) * | 2019-03-20 | 2019-06-21 | 华南理工大学 | Decelerating motor product examine method based on empirical mode decomposition and octave spectrum analysis |
CN109977477A (en) * | 2019-02-28 | 2019-07-05 | 清华大学 | Based on the Utility Boiler Superheater health state evaluation method for improving Fuzzy Level Analytic Approach |
CN110287921A (en) * | 2019-06-28 | 2019-09-27 | 潍柴动力股份有限公司 | A kind of noise-reduction method and noise reduction system of engine features parameter |
CN110686899A (en) * | 2019-09-21 | 2020-01-14 | 天津大学 | Internal combustion engine noise source identification method |
EP3626954A1 (en) * | 2018-09-20 | 2020-03-25 | IFP Energies nouvelles | Method for determining an indicator of knocking by determining the overall pressure in the cylinder |
CN110991017A (en) * | 2019-11-19 | 2020-04-10 | 南京航空航天大学 | Flight/propulsion system/jet noise comprehensive real-time model modeling method |
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CN113806991A (en) * | 2021-11-17 | 2021-12-17 | 天津仁爱学院 | Engine combustion noise optimization prediction method and device and storage medium |
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